datasynth-core
Core domain models, traits, and distributions for synthetic accounting data generation.
Overview
datasynth-core provides the foundational building blocks for the SyntheticData workspace:
- Domain Models: Journal entries, chart of accounts, master data, documents, anomalies
- Statistical Distributions: Line item sampling, amount generation, temporal patterns
- Core Traits: Generator and Sink interfaces for extensibility
- Template System: File-based templates for regional/sector customization
- Infrastructure: UUID factory, memory guard, GL account constants
Key Components
Domain Models (models/)
| Module | Description |
|---|---|
journal_entry.rs |
Journal entry header and balanced line items |
chart_of_accounts.rs |
Hierarchical GL accounts with account types |
master_data.rs |
Enhanced vendors, customers with payment behavior |
documents.rs |
Purchase orders, invoices, goods receipts, payments |
temporal.rs |
Bi-temporal data model for audit trails |
anomaly.rs |
Anomaly types and labels for ML training |
internal_control.rs |
SOX 404 control definitions |
Statistical Distributions (distributions/)
| Distribution | Description |
|---|---|
LineItemSampler |
Empirical distribution (60.68% two-line, 88% even counts) |
AmountSampler |
Log-normal with round-number bias, Benford compliance |
TemporalSampler |
Seasonality patterns with industry integration |
BenfordSampler |
First-digit distribution following P(d) = log10(1 + 1/d) |
Infrastructure
| Component | Description |
|---|---|
uuid_factory.rs |
Deterministic FNV-1a hash-based UUID generation |
memory_guard.rs |
Cross-platform memory tracking with soft/hard limits |
accounts.rs |
Centralized GL control account numbers |
templates/ |
YAML/JSON template loading and merging |
Usage
use ;
use AmountSampler;
// Create a balanced journal entry
let mut entry = new;
entry.add_line;
entry.add_line;
// Sample realistic amounts
let sampler = new;
let amount = sampler.sample_benford_compliant;
License
Apache-2.0 - See LICENSE for details.